Methods and apparatus to determine media impressions using distributed demographic information

ABSTRACT

Examples to log media impressions include extracting first and second cookie identifiers from a message received at a first Internet domain from a client device, the first cookie identifier associated with the first Internet domain, and the second cookie identifier associated with a second Internet domain outside the first Internet domain; and mapping the first cookie identifier to the second cookie identifier.

RELATED APPLICATION

This patent arises from a divisional of U.S. patent application Ser. No.13/921,962, filed Jun. 19, 2013, which claims priority to InternationalPatent Application Serial No. PCT/US11/65881, filed Dec. 19, 2011, whichclaims priority to U.S. Provisional Patent Application No. 61/424,952,filed on Dec. 20, 2010, which are hereby incorporated herein byreference in their entireties.

FIELD OF THE DISCLOSURE

The present disclosure relates generally to monitoring media and, moreparticularly, to methods and apparatus to determine media impressionsusing distributed demographic information.

BACKGROUND

Traditionally, audience measurement entities determine audienceengagement levels for media programming based on registered panelmembers. That is, an audience measurement entity enrolls people whoconsent to being monitored into a panel. The audience measurement entitythen monitors those panel members to determine media programs (e.g.,television programs or radio programs, movies, DVDs, etc.) exposed tothose panel members. In this manner, the audience measurement entity candetermine exposure measures for different media content based on thecollected media measurement data.

Techniques for monitoring user access to Internet resources such as webpages, advertisements and/or other content has evolved significantlyover the years. Some known systems perform such monitoring primarilythrough server logs. In particular, entities serving content on theInternet can use known techniques to log the number of requests receivedfor their content at their server.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an example system to determine advertisement and/orcontent impressions using distributed demographic information.

FIG. 2 depicts an example manner of reporting cookies to an audiencemeasurement entity and database proprietor(s) in response to userslogging in to website(s) of the database proprietor(s).

FIG. 3 depicts an example manner in which a web browser can reportimpressions to an impression monitor of the example system of FIG. 1.

FIG. 4 is an example apparatus that may be used to associate impressionswith demographics of users registered with one or more databaseproprietors.

FIG. 5 is an example partner cookie map that may be used by an Internetservice database proprietor to map user identifiers associated with anaudience measurement entity with user identifiers of users registeredwith the Internet service database proprietor.

FIG. 6 is an example impressions table generated by the impressionmonitor system of the example system of FIG. 1 to correlate impressionswith user identifiers of monitored audience members.

FIG. 7 depicts an example partner-based impressions table generated byan Internet service database proprietor to correlate impressions withuser identifiers of registered users of the Internet service databaseproprietors.

FIG. 8 depicts an example impressions table showing quantities ofimpressions associated with monitored users.

FIG. 9 depicts an example campaign-level age/gender and impressioncomposition table generated by a database proprietor.

FIG. 10 is a flow diagram representative of example machine readableinstructions that may be executed to report login events and usercookies to database proprietors.

FIG. 11 is a flow diagram representative of example machine readableinstructions that may be executed to map audience measurement entity(AME) cookie identifiers to user identifiers of users registered with adatabase proprietor.

FIG. 12 is a flow diagram representative of example machine readableinstructions that may be executed to log impressions.

FIG. 13 is a flow diagram representative of example machine readableinstructions that may be executed to generate demographics-basedimpressions reports.

FIG. 14 is an example processor system that can be used to execute theexample instructions of FIGS. 10-13 to implement the example apparatusand systems of FIGS. 1, 2, 3, and/or 4.

FIG. 15 is an example apparatus that may be used to implement theimpression monitor of FIGS. 1-3.

FIG. 16 is an example apparatus that may be used to implement a cookiereporter of FIG. 2.

DETAILED DESCRIPTION

Techniques for monitoring user access to Internet resources such as webpages, advertisements and/or other content has evolved significantlyover the years. At one point in the past, such monitoring was doneprimarily through server logs. In particular, entities serving contenton the Internet would log the number of requests received for theircontent at their server. Basing Internet usage research on server logsis problematic for several reasons. For example, server logs can betampered with either directly or via zombie programs that repeatedlyrequest content from the server to increase the server log counts.Secondly, content is sometimes retrieved once, cached locally and thenrepeatedly viewed from the local cache without involving the server inthe repeat viewings. Server logs cannot track these views of cachedcontent. Thus, server logs are susceptible to both over-counting andunder-counting errors.

The inventions disclosed in Blumenau, U.S. Pat. No. 6,108,637,fundamentally changed the way Internet monitoring is performed andovercame the limitations of the server side log monitoring techniquesdescribed above. For example, Blumenau disclosed a technique whereinInternet content to be tracked is tagged with beacon instructions (e.g.,tag instructions). In particular, monitoring instructions are associatedwith the HTML of the content (e.g., advertisements or other Internetcontent) to be tracked. When a client requests the content, both thecontent and the beacon or tag instructions are downloaded to the clienteither simultaneously (e.g., with the tag instructions present in theHTML) or via subsequent requests (e.g., via execution of a request toretrieve the monitoring instructions embedded in the HTML of thecontent). The tag instructions are, thus, executed whenever the contentis accessed, be it from a server or from a cache.

The tag instructions cause monitoring data reflecting information aboutthe access to the content to be sent from the client that downloaded thecontent to a monitoring entity. The monitoring entity may be an audiencemeasurement entity that did not provide the content to the client andwho is a trusted third party for providing accurate usage statistics(e.g., The Nielsen Company, LLC). Advantageously, because the taginstructions are associated with the content (e.g., embedded in orotherwise linked to some portion of the content) and executed by theclient browser whenever the content is accessed, the monitoringinformation is provided to the audience measurement company irrespectiveof whether the client is a panelist of the audience measurement company.

In some instances, it is important to link demographics to themonitoring information. To address this issue, the audience measurementcompany establishes a panel of users who have agreed to provide theirdemographic information and to have their Internet browsing activitiesmonitored. When an individual joins the panel, they provide detailedinformation concerning their identity and demographics (e.g., gender,race, income, home location, occupation, etc.) to the audiencemeasurement company. The audience measurement entity sets a cookie(e.g., a panelist cookie) on the panelist computer that enables theaudience measurement entity to identify the panelist whenever thepanelist accesses tagged content (e.g., content associated with beaconor tag instructions) and, thus, sends monitoring information to theaudience measurement entity.

Since most of the clients providing monitoring information from thetagged pages are not panelists and, thus, are unknown to the audiencemeasurement entity, it has heretofore been necessary to use statisticalmethods to impute demographic information based on the data collectedfor panelists to the larger population of users providing data for thetagged content. However, panel sizes of audience measurement entitiesremain small compared to the general population of users. Thus, aproblem is presented as to how to increase panel sizes while ensuringthe demographics data of the panel is accurate.

There are many database proprietors operating on the Internet. Thesedatabase proprietors provide services to large numbers of subscribers orregistered users. In exchange for the provision of the service, thesubscribers register with the proprietor. As part of this registration,the subscribers provide detailed demographic information. Examples ofsuch database proprietors include social network providers such asFacebook, Myspace, etc. These database proprietors set cookies on thecomputing device (e.g., computer, cell phone, etc.) of their subscribersto enable the database proprietors to recognize the users when theyvisit their websites.

The protocols of the Internet make cookies inaccessible outside of thedomain (e.g., Internet domain, domain name, etc.) on which they wereset. Thus, a cookie set in the HFZlaw.com domain is accessible toservers in the HFZlaw.com domain, but not to servers outside thatdomain. Therefore, although an audience measurement entity might find itadvantageous to access the cookies set by the database proprietors, theyare unable to do so.

In view of the foregoing, it would be advantageous to leverage theexisting databases of database proprietors to collect more extensiveInternet usage and demographic data. However, there are several problemsin accomplishing this end. For example, a problem is presented as to howto access the data of the database proprietors without compromising theprivacy of the subscribers, the panelists, and/or the proprietors of thetracked content. Another problem is how to access this data given thetechnical restrictions imposed by the Internet protocols that preventthe audience measurement entity from accessing cookies set by thedatabase proprietor. Example methods, apparatus and articles ofmanufacture disclosed herein solve these problems by extending thebeaconing process to encompass partnered database proprietors and byusing such partners as sources of distributed demographic information.

Example methods, apparatus, systems, and/or articles of manufacturedisclosed herein cooperate with one or more database proprietors (alsoreferred to herein as partners). The database proprietors provideInternet services to their registered users (e.g., users of thosedatabase proprietors) and store demographic information (e.g., in useraccount records) for those registered users. As part of this effort, thedatabase proprietor agrees to provide demographic information of itsregistered users to the audience measurement entity for purposes ofmeasuring demographic-based exposures to media such as content and/oradvertisements. To prevent violating privacy agreements with theregistered users of the database proprietor, examples disclosed hereinemploy cookie mapping techniques. That is, the database proprietor canmaintain a mapping of its registered user cookies (i.e., partner cookiesassigned by the database proprietor to its registered users) to cookiesassigned by the audience measurement entity (i.e., audience measuremententity (AME) cookies) to the same registered users. In this manner, theaudience measurement entity can log impressions of registered usersbased on the AME cookies and send full or partial AME cookie-basedimpression logs to a database proprietor. The database proprietor can,in turn, match its registered users to the AME cookie-based impressionsbased on its partner-to-AME cookie map. The database proprietor can thenuse the matches to associate demographic information for the matchingregistered users with corresponding impression logs. The databaseproprietor can then remove any identifying data (i.e., partner cookiedata) from the demographic-based impression logs and provide thedemographic-based impression logs to the audience measurement entitywithout revealing the identities of the database proprietor's registeredusers to the audience measurement entity. Thus, example techniquesdisclosed herein may be implemented without compromising privacies ofregistered users of database proprietors that partner with an audiencemeasurement entity to track impressions based on audience demographics.

A database proprietor (e.g., Facebook) can access cookies it has set ona client device (e.g., a computer) to thereby identify the client basedon the internal records (e.g., user account records) of the databaseproprietor. Because the identification of client devices is done withreference to enormous databases of registered users far beyond thequantity of persons present in a typical audience measurement panel,this process may be used to develop data that is extremely accurate,reliable, and detailed.

Because the audience measurement entity remains the first leg of thedata collection process (i.e., receives tag requests generated by taginstructions from client devices to log impressions), the audiencemeasurement entity is able to obscure the source of the content accessbeing logged as well as the identity of the content (e.g.,advertisements and/or other types of media) itself from the databaseproprietors (thereby protecting the privacy of the content sources),without compromising the ability of the database proprietors to providedemographic information corresponding to ones of their subscribers forwhich the audience measurement entity logged impressions.

Example methods, apparatus, and/or articles of manufacture disclosedherein can be used to determine impressions or exposures toadvertisements and/or other types of media such as content usingdemographic information, which is distributed across different databases(e.g., different website owners, different service providers, etc.) onthe Internet. Not only do example methods, apparatus, and articles ofmanufacture disclosed herein enable more accurate correlation ofdemographics to media impressions, but they also effectively extendpanel sizes and compositions beyond persons participating (and/orwilling to participate) in the panel of a ratings entity to personsregistered in other Internet databases such as the databases of socialmedia sites such as Facebook, Twitter, Google, etc. This extensioneffectively leverages the content tagging capabilities of the audienceratings entity and the use of databases of non-ratings entities such associal media and other websites to create an enormous, demographicallyaccurate panel that results in accurate, reliable measurements ofexposures to Internet content such as advertising and/or programming.

Traditionally, audience measurement entities (also referred to herein as“ratings entities”) determine demographic reach for advertising andmedia programming based on registered panel members. That is, anaudience measurement entity enrolls people that consent to beingmonitored into a panel. During enrollment, the audience measuremententity receives demographic information from the enrolling people sothat subsequent correlations may be made between advertisement/mediaexposure to those panelists and different demographic markets. Unliketraditional techniques in which audience measurement entities relysolely on their own panel member data to collect demographics-basedaudience measurements, example methods, apparatus, and/or articles ofmanufacture disclosed herein enable an audience measurement entity toobtain demographic information from other entities that operate based onuser registration models. As used herein, a user registration model is amodel in which users subscribe to services of those entities by creatinguser accounts and providing demographic-related information aboutthemselves. Obtaining such demographic information associated withregistered users of database proprietors enables an audience measuremententity to extend or supplement its panel data with substantiallyreliable demographics information from external sources (e.g., databaseproprietors), thus extending the coverage, accuracy, and/or completenessof their demographics-based audience measurements. Such access alsoenables the audience measurement entity to monitor persons who would nototherwise have joined an audience measurement panel.

Any entity having a database identifying demographics of a set ofindividuals may cooperate with the audience measurement entity. Suchentities are referred to herein as “database proprietors” and includeentities such as Facebook, Google, Yahoo!, MSN, Twitter, Apple iTunes,Experian, etc. Such database proprietors may be, for example, online webservices providers. For example, a database proprietor may be a socialnetwork site (e.g., Facebook, Twitter, MySpace, etc.), a multi-servicesite (e.g., Yahoo!, Google, Experian, etc.), an online retailer site(e.g., Amazon.com, Buy.com, etc.), and/or any other web services sitethat maintains user registration records and irrespective of whether thesite fits into none, one or more of the categories noted above.

Example methods, apparatus, and/or articles of manufacture disclosedherein may be implemented by an audience measurement entity, a ratingsentity, or any other entity interested in measuring or tracking audienceexposures to advertisements and/or any other media.

To increase the likelihood that measured viewership is accuratelyattributed to the correct demographics, example methods, apparatus,and/or articles of manufacture disclosed herein use demographicinformation located in the audience measurement entity's records as wellas demographic information located at one or more database proprietors(e.g., web service providers) that maintain records or profiles of usershaving accounts therewith. In this manner, example methods, apparatus,and/or articles of manufacture may be used to supplement demographicinformation maintained by a ratings entity (e.g., an audiencemeasurement company such as The Nielsen Company of Schaumburg, Ill.,United States of America, that collects media exposure measurementsand/or demographics) with demographic information from one or moredifferent database proprietors (e.g., web service providers).

The use of demographic information from disparate data sources (e.g.,high-quality demographic information from the panels of an audiencemeasurement company and/or registered user data of web serviceproviders) results in improving the reporting effectiveness of metricsfor online and/or offline advertising campaigns. Examples disclosedherein use online registration data to identify demographics of users.Such examples also use server impression counts, tagging (also referredto as beaconing), and/or other techniques to track quantities ofadvertisement and/or content impressions attributable to those users.Online web service providers such as social networking sites andmulti-service providers (collectively and individually referred toherein as online database proprietors) maintain detailed demographicinformation (e.g., age, gender, geographic location, race, income level,education level, religion, etc.) collected via user registrationprocesses. An impression corresponds to a home or individual having beenexposed to the corresponding media content and/or advertisement. Thus,an impression represents a home or an individual having been exposed toan advertisement or content or group of advertisements or content. InInternet advertising, a quantity of impressions or impression count isthe total number of times an advertisement or advertisement campaign hasbeen accessed by a web population (e.g., including number of timesaccessed as decreased by, for example, pop-up blockers and/or increasedby, for example, retrieval from local cache memory).

Example impression reports generated using example methods, apparatus,and/or articles of manufacture disclosed herein may be used to report TVGRPs and online GRPs in a side-by-side manner. For instance, advertisersmay use impression reports to report quantities of unique people orusers that are reached individually and/or collectively by TV and/oronline advertisements.

Although examples are disclosed herein in connection withadvertisements, advertisement exposures, and/or advertisementimpressions, such examples may additionally or alternatively beimplemented in connection with other types of media in addition to orinstead of advertisements. That is, processes, apparatus, systems,operations, structures, data, and/or information disclosed herein inconnection with advertisements may be similarly used and/or implementedfor use with other types of media such as content. “Media” refers tocontent and/or advertisements. Websites, movies, television and/or otherprogramming is generally referred to herein as content. Advertisementsare typically distributed with content. Traditionally, content isprovided at little or no cost to the audience because it is subsidizedby advertisers who pay to have their advertisements distributed with thecontent.

Turning now to FIG. 1, an example system 100 is shown. In theillustrated example, the system 100 includes an impression monitorsystem 102 which may be owned and/or operated by an audience measuremententity 103. In the illustrated examples, the impression monitor system102 works cooperatively with one or more database proprietors, two ofwhich are shown as a partner A database proprietor 104 a and a partner Bdatabase proprietor 104 b, to generate impression reports 106 a and 106b using distributed demographic information collected by the databaseproprietors 104 a and 104 b. In the illustrated example, the impressionreports 106 a and 106 b are indicative of demographic segments,populations, or groups that were exposed to identified advertisements orcontent. “Distributed demographics information” is used herein to referto demographics information obtained from a database proprietor such asan online web services provider. In the illustrated example, theimpression monitor system 102 may be owned and/or operated by anaudience measurement entity to collect and log impressions from clientdevices 108 using, for example, audience measurement entity (AME)cookies set on those client devices 108. In illustrated examplesdescribed herein, AME cookies (e.g., an AME cookie 208 of FIG. 2) areset in the client devices 108 in response to contacting the audiencemeasurement entity 103 after executing monitoring or tag instructionsregardless of whether all, some, or none of the client devices 108 areassociated with audience member panels of the audience measuremententity 103. That is, by setting AME cookies in the client devices 108,the audience measurement entity 103 is able to log ad and/or contentimpressions regardless of whether the ad and/or content impressions areattributable to panelists or non-panelists. In the illustrated exampleof FIG. 1, the client devices 108 may be stationary or portablecomputers, handheld computing devices, smart phones, Internetappliances, and/or any other type of device that may be connected to theInternet and capable of presenting media content.

In the illustrated example, content providers and/or advertisersdistribute advertisements 110 via the Internet to users that accesswebsites and/or online television services (e.g., web-based TV, Internetprotocol TV (IPTV), etc.). In the illustrated example, theadvertisements 110 may be individual, stand alone ads and/or may be partof one or more ad campaigns. The ads of the illustrated example areencoded with identification codes (i.e., data) that identify theassociated ad campaign (e.g., campaign ID, if any), a creative type ID(e.g., identifying a Flash-based ad, a banner ad, a rich type ad, etc.),a source ID (e.g., identifying the ad publisher), and/or a placement ID(e.g., identifying the physical placement of the ad on a screen). Theadvertisements 110 of the illustrated example are also tagged or encodedto include computer executable monitoring instructions (e.g., Java, javascript, or any other computer language or script) that are executed byweb browsers that access the advertisements 110 via, for example, theInternet. In the illustrated example of FIG. 1, the advertisements 110are presented to audience members via the client devices 108. Computerexecutable monitoring instructions may additionally or alternatively beassociated with content to be monitored. Thus, although this disclosurefrequently speaks in terms of tracking advertisements, it is notrestricted to tracking any particular type of media. On the contrary, itcan be used to track media (e.g., content and/or advertisements) of anytype or form in a network. Irrespective of the type of media beingtracked, execution of the monitoring instructions causes the web browserto send impression requests 112 (e.g., referred to herein as tagrequests 112) to a specified server (e.g., the audience measuremententity). The tag requests 112 may be implemented using HTTP requests.However, whereas HTTP requests traditionally identify web pages or otherresources to be downloaded, the tag requests 112 of the illustratedexample include audience measurement information (e.g., ad campaignidentification, content identifier, and/or user identificationinformation) as their payloads. The server (e.g., the impression monitorsystem 102) to which the tag requests 112 are directed is programmed tolog the audience measurement data caused by the tag requests 112 asimpressions (e.g., ad and/or content impressions depending on the natureof the media tagged with the monitoring instructions). To collect andlog exposure measurements, the impression monitor system 102 includes anAME impressions store 114. Example impression logging processes aredescribed in detail below in connection with FIG. 3.

In some examples, advertisements tagged with such tag instructions aredistributed with Internet-based media content such as, for example, webpages, streaming video, streaming audio, IPTV content, etc. As notedabove, methods, apparatus, systems, and/or articles of manufacturedisclosed herein are not limited to advertisement monitoring but can beadapted to any type of content monitoring (e.g., web pages, movies,television programs, etc.) Example techniques that may be used toimplement such monitoring, tag and/or beacon instructions are describedin Blumenau, U.S. Pat. No. 6,108,637, which is hereby incorporatedherein by reference in its entirety.

In the illustrated example of FIG. 1, the impression monitor system 102tracks users associated with impressions using AME cookies (e.g.,name-value pairs of Universally Unique Identifiers (UUIDs)) when theclient devices 108 present advertisements (e.g., the advertisements 110)and/or other content. Due to Internet security protocols, the impressionmonitor system 102 can only collect cookies set in its domain (e.g., AMEcookies). Thus, if, for example, the impression monitor system 102operates in the “Nielsen.com” domain, it can only collect cookies set inthe Nielsen.com domain. Thus, when the impression monitor system 102receives tag requests 112 from the client devices 108, the impressionmonitor system 102 only has access to AME cookies set on that clientdevice for, for example, the Nielsen.com domain, but not cookies setoutside its domain (e.g., outside the Nielsen.com domain).

To overcome the domain limitations associated with collecting cookieinformation, the impression monitoring system 102 monitors impressionsof users of the client devices 108 that are registered users of one orboth of the partner A and partner B database proprietors 104 a and 104b. When a user of one of the client devices 108 logs into a service ofone of the database proprietors 104 a or 104 b, the client device 108performs an initialization (INIT) AME cookie message exchange 116 withthe impression monitor system 102 and sends a login reporting message118 to the database proprietor providing that service. For example, asdescribed in more detail below in connection with FIG. 2, if a user logsinto a service of the partner A database proprietor 104 a, the INIT AMEcookie message exchange 116 sets an AME cookie in the client device 108based on the domain of the impression monitor system 102 for the userthat logged into the service of the partner A database proprietor 104 a.In addition, the login reporting message 118 sent to the partner Adatabase proprietor 104 a includes the same AME cookie for the clientdevice 108 and a partner A cookie set by the partner A databaseproprietor 104 a for the same client device 108. In the illustratedexample, the partner A database proprietor 104 a sets the partner Acookie in the client device 108 when the client device 108 visits awebpage of the partner A database proprietor 104 a and/or when a userlogs into a service of the partner A database proprietor 104 a via alogin page of the partner A database proprietor 104 a (e.g., the loginwebpage 204 of FIG. 2). In the illustrated example, the AME cookie isoutside a domain (e.g., a root domain) of the partner A cookie. Thelogin reporting message 118 enables the partner A database proprietor104 a to map its partner A cookie to the AME cookie for the user of theclient device 108. The INIT AME cookie message exchange 116 includes alogin timestamp indicative of when a user associated with the specifiedAME cookie logged into the partner A database proprietor 104 a. If anAME cookie was previously set for the client, a new AME cookie is notset unless the previous AME cookie has been removed from the client, isnot longer present on the client, and/or has expired. These processesare described in greater detail below in connection with FIG. 2.

Subsequently, the impression monitor system 102 receives the tagrequests 112 based on ads and/or content presented via the clientdevices 108 and logs impressions based on the presented ads and/orcontent in association with respective AME cookies of the client devices108 as described in detail below in connection with FIG. 3. In theillustrated example of FIG. 1, the impression monitor system 102 storesthe logged impressions in the AME impressions store 114 and subsequentlysends AME impression logs 122 containing some or all of the loggedimpressions from the AME impressions store 114 to the partner databaseproprietors 104 a and 104 b.

Each of the partner database proprietors 104 a-b may subsequently usetheir respective AME cookie-to-partner cookie mappings to matchdemographics of users of the client devices 108 identified based onpartner cookies with impressions logged based on AME cookies in the AMEimpression logs 122. Example demographic matching and reporting isdescribed in greater detail below in connection with FIG. 4. Because theaudience measurement entity 103 sets AME cookies on any client thatsends it a tag request (i.e., including non-panelists), the map of theAME cookies to partner cookies is not limited to panelists but insteadextends to any client that accesses tagged media. As a result, theaudience measurement entity 103 is able to leverage the data of thepartner as if the non-panelists with AME cookies were panelists of theaudience measurement entity 103, thereby effectively increasing thepanel size. In some examples, the panel of the audience measuremententity is eliminated.

FIG. 2 depicts an example manner of setting cookies with the impressionmonitor system 102 and reporting the same to the database proprietors(e.g., the partner A database proprietor 104 a and/or the partner Bdatabase proprietor 104 b) in response to users logging in to websitesof the database proprietors. One of the client devices 108 of FIG. 1 isshown in FIG. 2 and is provided with a cookie reporter 202 configured tomonitor login events on the client device 108 and to send cookies to theimpression monitor system 102 and the database proprietors 104 a and 104b. In the illustrated example of FIG. 2, the cookie reporter 202 isshown performing the INIT AME cookie message exchange 116 with theimpression monitor system 102 and sending the login reporting message118 to the partner A database proprietor 104 a.

In the illustrated example of FIG. 2, the cookie reporter 202 isimplemented using computer executable instructions (e.g., Java, javascript, or any other computer language or script) that are executed byweb browsers. Also in the illustrated example of FIG. 2, the cookiereporter 202 is provided to the clients, directly or indirectly, by anaudience measurement entity that owns and/or operates the impressionmonitor system 102. For example, the cookie reporter 202 may be providedto the database proprietor from the AME 103 and subsequently downloadedto the client device 108 from a server serving a login webpage 204 ofthe partner A database proprietor 104 a (or of the partner B databaseproprietor 104 b or of any other partner database proprietor) inresponse to the client device 108 requesting the login webpage.

A web browser of the client device 108 may execute the cookie reporter202 to monitor for login events associated with the login page 204. Whena user logs in to a service of the partner A database proprietor 104 avia the login page 204, the cookie reporter 202 initiates the INIT AMEmessage exchange 116 by sending a request 206 to the impression monitorsystem 102. In the illustrated example of FIG. 2, the request 206 is adummy request because its purpose is not to actually retrieve a webpage,but is instead to cause the impression monitor system 102 to generate anAME cookie 208 for the client device 108 (assuming an AME cookie has notalready been set for and/or is not present on the client). The AMEcookie 208 uniquely identifies the client device 108. However, becausethe client device 108 may not be associated with a panelist of the AME103, the identity and/or characteristics of the user may not be known.The impression monitor system 102 subsequently uses the AME cookie 208to track or log impressions associated with the client device 108,irrespective of whether the client device 108 is a panelist of the AME103, as described below in connection with FIG. 3. Because disclosedexamples monitor clients as panelists even though they may not have beenregistered (i.e., have not agreed to be a panelist of the AME 103), suchclients may be referred to herein as pseudo-panelists.

The request 206 of the illustrated example is implemented using an HTTPrequest that includes a header field 210, a cookie field 212, and apayload field 214. The header field 210 stores standard protocolinformation associated with HTTP requests. When the client device 108does not yet have an AME cookie set therein, the cookie field 212 isempty to indicate to the impression monitor system 102 that it needs tocreate and set the AME cookie 208 in the client device 108. In responseto receiving a request 206 that does not contain an AME cookie 208, theimpression monitor system 102 generates an AME cookie 208 and sends theAME cookie 208 to the client device 108 in a cookie field 218 of aresponse message 216 as part of the INIT AME cookie message exchange 116of FIG. 1 to thereby set the AME cookie 208 in the client device 108.

In the illustrated example of FIG. 2, the impression monitor system 102also generates a login timestamp 220 indicative of a time at which auser logged in to the login page 204 and sends the login timestamp 220to the client device 208 in a payload field 222 of the response 216. Inthe illustrated example, the login timestamp 220 is generated by theimpression monitor system 102 (e.g., rather than the client device 108)so that all login events from all client devices 108 are time stampedbased on the same clock (e.g., a clock of the impression monitor system102). In this manner, login times are not skewed or offset based onclocks of respective client devices 108, which may have differences intime between one another. In some examples, the timestamp 220 may beomitted from the payload 222 of the response 216, and the impressionmonitor system 102 may instead indicate a login time based on atimestamp in a header field 224 of the response 216. In some examples,the response 216 is an HTTP 302 redirect response which includes a URL226 of the partner A database proprietor 104 a to which the cookiereporter 202 should send the AME cookie 208. The impression monitorsystem 102 populates the redirect response with the URL.

In the illustrated example of FIG. 2, after receiving the response 216,the cookie reporter 202 generates and sends the login reporting message118 to the partner A database proprietor 104 a. For example, the cookiereporter 202 of the illustrated example sends the login reportingmessage 118 to a URL indicated by the login page 204. Alternatively, ifthe response 216 is an HTTP 302 redirect and includes the URL 226, thecookie reporter 202 sends the login reporting message 118 to the partnerA database proprietor 104 a using the URL 226. In the illustratedexample of FIG. 2, the login reporting message 118 includes a partner Acookie 228 in a cookie field 230. The partner A cookie 228 uniquelyidentifies the client device 108 for the partner A database proprietor104 a. Also in the illustrated example, the cookie reporter 202 sendsthe AME cookie 208 and the login timestamp 220 in a payload field 232 ofthe login reporting message 118. Thus, in the illustrated example ofFIG. 2, the AME cookie 208 is sent as regular data (e.g., a dataparameter) or payload in the login reporting message 118 to the partnerA database proprietor 104 a to overcome the fact that the AME cookie 208was not set in the domain of the partner A database proprietor 104 a. Inthe illustrated example, the AME cookie 208 corresponds to anotherdomain (e.g., a Nielsen.com root domain) outside the domain of thepartner A cookie 228 (e.g., a Facebook.com root domain). Using exampleprocesses illustrated in FIG. 2 advantageously enables sending cookiedata across different domains, which would otherwise not be possibleusing known cookie communication techniques. The database proprietor 104a receives the AME cookie 208 in association with the partner A cookie228, thereby, creating an entry in an AME cookie-to-partner cookie map(e.g., the partner cookie map 236).

Although the login reporting message 118 is shown in the example of FIG.2 as including the partner A cookie 228, for instances in which thepartner A database proprietor 104 a has not yet set the partner A cookie228 in the client device 108, the cookie field 230 is empty in the loginreporting message 118. In this manner, the empty cookie field 230prompts the partner A database proprietor 104 a to set the partner Acookie 228 in the client device 108. In such instances, the partner Adatabase proprietor 104 a sends the client device 108 a response message(not shown) including the partner A cookie 228 and records the partner Acookie 228 in association with the AME cookie 208.

In some examples, the partner A database proprietor 104 a uses thepartner A cookie 228 to track online activity of its registered users.For example, the partner A database proprietor 104 a may track uservisits to web pages hosted by the partner A database proprietor 104 a,display those web pages according to the preferences of the users, etc.The partner A cookie 228 may also be used to collect “domain-specific”user activity. As used herein, “domain-specific” user activity is userInternet activity associated within the domain(s) of a single entity.Domain-specific user activity may also be referred to as “intra-domainactivity.” In some examples, the partner A database proprietor 104 acollects intra-domain activity such as the number of web pages (e.g.,web pages of the social network domain such as other social networkmember pages or other intra-domain pages) visited by each registereduser and/or the types of devices such as mobile devices (e.g., smartphones) or stationary devices (e.g., desktop computers) used for access.The partner A database proprietor 104 a may also track accountcharacteristics such as the quantity of social connections (e.g.,friends) maintained by each registered user, the quantity of picturesposted by each registered user, the quantity of messages sent orreceived by each registered user, and/or any other characteristic ofuser accounts.

In some examples, the cookie reporter 202 is configured to send therequest 206 to the impression monitor system 102 and send the loginreporting message 118 to the partner A database proprietor 104 a onlyafter the partner A database proprietor 104 a has indicated that a userlogin via the login page 204 was successful. In this manner, the request206 and the login reporting message 118 are not performed unnecessarilyshould a login be unsuccessful. In the illustrated example of FIG. 2, asuccessful login ensures that the partner A database proprietor 104 awill associate the correct demographics of a logged in registered userwith the partner A cookie 228 and the AME cookie 208.

In the illustrated example of FIG. 2, the partner A database proprietor104 a includes a server 234, a partner cookie map 236, and a useraccounts database 238. Although not shown, other database proprietors(e.g., the partner B database proprietor 104 b of FIG. 1) that partnerwith the audience measurement entity 103 (FIG. 1) also include arespective partner cookie map similar to the partner cookie map 236 anda user accounts database similar to the user accounts database 238 but,of course, relative to their own users. The server 234 of theillustrated example communicates with the client device 108 to, forexample, receive login information, receive cookies from the clientdevice 108, set cookies in the client device 108, etc.

The partner cookie map 236 stores partner cookies (e.g., the partner Acookie 228) in association with respective AME cookies (e.g., the AMEcookie 208) and respective timestamps (e.g., the timestamp 220). In theillustrated example of FIG. 2, the partner cookie map 236 stores aunique user ID (UUID) found in a name-value pair (i.e., a parameter namesuch as ‘user ID’ and a value such as the UUID) of the partner A cookie228 in association with a unique user ID found in a name-value pair ofthe AME cookie 208. In addition, the partner cookie map 236 stores thelogin timestamp 220 in association with the UUIDs to indicate a time atwhich a corresponding user login occurred. Referring briefly to FIG. 5,an example implementation of the partner cookie map 236 is shown, inwhich an AME user ID column 502 stores UUIDs from AME cookies (e.g., theAME cookie 208 of FIG. 2), a partner user ID column 504 stores UUIDsfrom partner cookies (e.g., the partner A cookie 228 of FIG. 2), and alogin timestamp column 506 stores login timestamps (e.g., the logintimestamp 220 of FIG. 2). In illustrated examples disclosed herein, thepartner A database proprietor 104 a uses the partner cookie map 236 tomatch impressions received from the impression monitor system 102 basedon AME cookies (e.g., the AME cookie 208) to registered users of thepartner A database proprietor 104 a identified by respective partner Acookies (e.g., the partner A cookie 228). In this manner, the partner Adatabase proprietor 104 a can determine which of its registered usersare associated with specific impressions logged by the impressionmonitor system 102.

Returning to FIG. 2, the partner A database proprietor 104 a uses theuser accounts database 238 to store, among other things, demographicinformation for registered users of the partner A database proprietor104 a. In the illustrated example of FIG. 2, such demographicinformation is received from registered users during an enrollmentand/or registration process or during a subsequent personal informationupdate process. The demographic information stored in the user accountsdatabase 238 may include, for example, age, gender, interests (e.g.,music interests, movie interests, product interests, or interestsassociated with any other topic), number of friends or socialconnections maintained by each registered user via the partner Adatabase proprietor 104 a, personal yearly income, household income,geographic location of residence, geographic location of work,graduation year(s), quantity of group associations, or any otherdemographic information. The partner A database proprietor 104 a usesthe user accounts database 238 to associate demographic information toparticular impressions logged by the impression monitor system 102 afterdetermining which registered users of the partner A database proprietor104 a correspond to which logged impressions based on the partner cookiemap 236.

FIG. 3 depicts an example system 300 that may be used to log impressionsat the impression monitor system 102 of the example system 100 ofFIG. 1. The example system 300 enables the impressions monitor system102 of FIGS. 1 and 2 to log impressions in association withcorresponding AME cookies (e.g., the AME cookie 208 of FIG. 2) based ontag requests (e.g., the tag requests 112 of FIG. 1) received from a webbrowser 302 executed by a client device (e.g., any client device 108 ofFIGS. 1 and 2). In the illustrated example of FIG. 3, the impressionmonitor system 102 logs impressions from any client device (e.g., theclient devices 108 of FIG. 1) from which it receives a tag request 112as described below. The impression monitor system 102 compiles thereceived impression data in the AME impression data store 114.

Turning in detail to FIG. 3, the client device may be any one of theclient devices 108 of FIGS. 1 and 2 or another device not shown in FIG.1 or 2. However, for simplicity of discussion and without loss ofgenerality, the client device will be referred to as client device 108.As shown, the client device 108 sends communications to the impressionsmonitor system 102. In the illustrated example, the client device 108executes the web browser 302, which is directed to a host website (e.g.,www.acme.com) that displays one of the advertisement(s) 110 receivedfrom an ad publisher 303. The advertisement 110 of the illustratedexample is tagged with identifier information (e.g., a campaign ID, acreative type ID, a placement ID, a publisher source URL, etc.) and taginstructions 304. When the tag instructions 304 are executed by theclient device 108, the tag instructions 304 cause the client device 108to send a tag request 112 to a URL address of the impressions monitorsystem 102 as specified in the tag instructions 304. Alternatively, theURL address specified in the tag instructions 304 may direct the tagrequest 112 to any other server owned, operated, and/or accessible bythe audience measurement entity 103 (FIG. 1) or another entity. The taginstructions 304 may be implemented using java script or any othertype(s) of executable instruction(s) including, for example, Java, HTML,etc. It should be noted that tagged content such as web pages, and/orany other media are processed the same way as the tagged advertisement110. That is, for any tagged media, corresponding tag instructions arereceived in connection with the download of the tagged content and causea tag request to be sent from the client device that downloaded thetagged content to the impression monitor system 102 (or any other serverindicated by the instructions).

In the illustrated example of FIG. 3, the tag request 112 is implementedusing an HTTP request and is shown in detail as including a header field310, a cookie field 312, and a payload field 314. In the illustratedexample of FIG. 3, the web browser 302 stores the AME cookie 208 of FIG.2 in the cookie field 312 and stores ad campaign information 316 and apublisher site ID 318 in the payload field 314. In the illustratedexample, the ad campaign information 316 may include informationidentifying one or more of an associated ad campaign (e.g., an adcampaign ID), a creative type ID (e.g., identifying a Flash-based ad, abanner ad, a rich type ad, etc.), and/or a placement ID (e.g.,identifying the physical placement of the ad on a screen). In someexamples, to log a content impression, the ad campaign information 316is replaced with content information indentifying the content (e.g., acontent identifier), a creative ID, and/or a placement ID. In theillustrated example, the publisher site ID 318 identifies a source ofthe advertisement 110 and/or content (e.g., a source ID identifying thead publisher 303 and/or content publisher).

In the illustrated example, in response to receiving the tag request112, the impression monitor system 102 logs an impression associatedwith the client device 108 in the AME impressions store 114 by storingthe AME cookie 208 in association with a content identifier (e.g., thead campaign information 316 and/or the publisher site ID 318). Inaddition, the impression monitor system 102 generates a timestampindicative of the time/date of when the impression occurred and storesthe timestamp in association with the logged impression. An exampleimplementation of the example AME impression store 114 is shown in FIG.6. Turning briefly to FIG. 6, the AME impression store 114 includes anAME user ID column 602 to store AME cookies (e.g., the AME cookie 208 ofFIGS. 2 and 3), a timestamp column 604 to store impression timestampsindicative of when impressions occurred at client devices (e.g., theclient device 108 of FIGS. 1-3), a campaign ID column 606 to store thecampaign information 316 of FIG. 3, and a site ID column 608 to storethe publisher site ID 318 of FIG. 3.

FIG. 4 is an example apparatus 400 that may be used to associateimpressions with demographics of users (e.g., users of the clientdevices 108 of FIGS. 1-3) registered with one or more databaseproprietors (e.g., the partner database proprietors 104 a-b of FIGS.1-3). In some examples, the apparatus 400 is implemented at one or moredatabase proprietors (e.g., the partner database proprietors 104 a-b ofFIGS. 1-3). Alternatively, the apparatus 400 may be implemented at othersites. In some examples, the apparatus 400 may be developed by theaudience measurement entity 103 (FIG. 1) and provided to a databaseproprietor to enable the database proprietor to combine databaseproprietor-owned demographic information with impression logs providedby the audience measurement entity 103. To ensure privacy of registeredusers of a database proprietor, the audience measurement entity 103 mayinstall or locate the example apparatus 400 at a database proprietor sothat the database proprietor need not provide identities of itsregistered users to the audience measurement entity 103 in order toassociate demographics information with logged impressions. Instead, theaudience measurement entity 103 can provide its logged impressions(e.g., the AME impression logs 122) to the database proprietor and thedatabase proprietor can associate respective demographics with thelogged impressions while concealing the identities (e.g., names andcontent information) of its registered users.

In the illustrated example, the apparatus 400 is provided with anexample cookie matcher 402, an example demographics associator 404, anexample demographics analyzer 406, an example demographics modifier 408,an example user ID modifier 410, an example report generator 412, anexample data parser 414, an example mapper 416, and an exampleinstructions interface 418. While an example manner of implementing theapparatus 400 has been illustrated in FIG. 4, one or more of theelements, processes and/or devices illustrated in FIG. 4 may becombined, divided, re-arranged, omitted, eliminated and/or implementedin any other way. Further, the cookie matcher 402, the demographicsassociator 404, the demographics analyzer 406, the demographics modifier408, the user ID modifier 410, the report generator 412, the data parser414, the mapper 416, the instructions interface 418 and/or, moregenerally, the example apparatus 400 of FIG. 4 may be implemented byhardware, software, firmware and/or any combination of hardware,software and/or firmware. Thus, for example, any of the cookie matcher402, the demographics associator 404, the demographics analyzer 406, thedemographics modifier 408, the user ID modifier 410, the reportgenerator 412, the data parser 414, the mapper 416, the instructionsinterface 418 and/or, more generally, the example apparatus 400 could beimplemented by one or more circuit(s), programmable processor(s),application specific integrated circuit(s) (ASIC(s)), programmable logicdevice(s) (PLD(s)) and/or field programmable logic device(s) (FPLD(s)),etc. When any of the apparatus or system claims of this patent are readto cover a purely software and/or firmware implementation, at least oneof the cookie matcher 402, the demographics associator 404, thedemographics analyzer 406, the demographics modifier 408, the user IDmodifier 410, the report generator 412, the data parser 414, the mapper416, and/or the instructions interface 418 are hereby expressly definedto include a tangible computer readable medium such as a memory, DVD,CD, BluRay disk, etc. storing the software and/or firmware. Furtherstill, the example apparatus 400 of FIG. 4 may include one or moreelements, processes and/or devices in addition to, or instead of, thoseillustrated in FIG. 4, and/or may include more than one of any or all ofthe illustrated elements, processes and devices.

Turning in detail to FIG. 4, in the illustrated example, the apparatus400 is implemented at the partner A database proprietor 104 a (FIGS. 1and 2). Other instances of the apparatus 400 could be similarlyimplemented at any other database proprietor participating with the AME103 (e.g., the partner B database proprietor 104 b). In the illustratedexample of FIG. 4, the apparatus 400 receives the AME impression logs122 from the impression monitor system 102 to enable the apparatus 400to associate user/audience member demographics from the user accountsdatabase 238 with logged impressions.

In the illustrated example, the apparatus 400 is provided with thecookie matcher 402 to match AME user IDs from AME cookies (e.g., the AMEcookie 208 of FIGS. 2 and 3) from the AME impression logs 122 to AMEuser IDs in the partner A cookie map 236. The apparatus 400 performssuch cookie matching to identify registered users of the partner Adatabase proprietor 104 a to which the logged impressions areattributable (e.g., partner A registered users for which the impressionmonitor system 102 set AME cookies as described above in connection withFIG. 2 and tracked impressions as described above in connection withFIG. 3). For example, the partner cookie map 236 is shown in FIG. 5 asassociating AME user IDs in the AME user ID column 502 to partner userIDs in the partner user ID column 504. The AME impression logs 122 arestructured similar to the data in the AME impression store 114 as shownin FIG. 6, which logs impressions per AME user ID. Thus, the cookiematcher 402 matches AME user IDs from the AME user ID column 602 of theAME impression logs 122 to AME user IDs of the AME user ID column 502 ofthe partner cookie map 236 to associate a logged impression from the AMEimpression logs 122 to a corresponding partner user ID mapped in thepartner cookie map 236 of FIG. 5. In some examples, the AME 103encrypts, obfuscates, varies, etc. campaign IDs in the AME impressionlogs 122 before sending the AME impression logs 122 to partner databaseproprietors (e.g., the partner database proprietors 104 a and 104 b ofFIGS. 1 and 2) to prevent the partner database proprietors fromrecognizing the content to which the campaign IDs correspond or tootherwise protect the identity of the content. In such examples, alookup table of campaign ID information may be stored at the impressionmonitor system 102 so that impression reports (e.g., the impressionreports 106 a and 106 b of FIG. 1) received from the partner databaseproprietors can be correlated with the content.

In some examples, the cookie matcher 402 uses login timestamps (e.g.,the login timestamp 220 of FIG. 2) stored in the login timestamp column506 of FIG. 5 and impression timestamps stored in the timestamp column604 of FIG. 6 to discern between different users to which impressionslogged by the impression monitor system 102 are attributable. That is,if two users having respective username/password login credentials forthe partner A database proprietor 104 a use the same client device 108,all impressions logged by the impression monitor system 102 will bebased on the same AME cookie (e.g., the AME cookie 208 of FIGS. 2 and 3)set in the client device 108 regardless of which user was using theclient device 108 when the impression occurred. However, by comparinglogged impression timestamps (e.g., in the timestamp column 604 of FIG.6) to login timestamps (e.g., in the login timestamp column 506 of FIG.5), the cookie matcher 402 can determine which user was logged into thepartner A database proprietor 104 a when a corresponding impressionoccurred. For example, if a user ‘TOM’ logged in to the partner Adatabase proprietor 104 a at 12:57 AM on Jan. 1, 2010 and a user ‘MARY’logged in to the partner A database proprietor 104 a at 3:00 PM on Jan.1, 2010 using the same client device 108, the login events areassociated with the same AME cookie (e.g., the AME cookie 208 of FIGS. 2and 3). In such an example, the cookie matcher 402 associates anyimpressions logged by the impression monitor system 102 for the same AMEcookie between 12:57 AM and 3:00 pm on Jan. 1, 2010 to the user TOM′ andassociates any impressions logged by the impression monitor system 102for the same AME cookie after 3:00 pm on Jan. 1, 2010 to the user‘MARY’. Such time-based associations are shown in the illustratedexample data structure of FIG. 7 described below.

In the illustrated example, the cookie matcher 402 compiles the matchedresults into an example partner-based impressions data structure 700,which is shown in detail in FIG. 7. Turning briefly to FIG. 7, thepartner-based impressions structure 700 includes an AME user ID column702, an impression timestamp column 704, a campaign ID column 706, asite ID column 708, a user login timestamp 710, and a partner user IDcolumn 712. In the AME user ID column 702, the cookie matcher 402 storesAME cookies (e.g., the AME cookie 208 of FIGS. 2 and 3). In theimpression timestamp column 704, the cookie matcher 402 storestimestamps generated by the impression monitor system 102 indicative ofwhen each impression was logged. In the campaign ID column 706, thecookie matcher 402 stores ad campaign IDs stored in, for example, thecampaign information 316 of FIG. 3. In some examples, instead of or inaddition to the campaign ID column 706, the partner-based impressionsdata structure 700 includes a content ID column to store identifyinginformation of content. In some examples, some content (e.g.,advertisements and/or other media) is not associated with a campaign IDor content ID. In the illustrated example of FIG. 7, blanks in thecampaign ID column 706 indicate content that is not associated withcampaign IDs and/or content IDs. In the site ID column 708, the cookiematcher 402 stores advertisement publisher site IDs (e.g., the publishersite ID 318 of FIG. 3). In the user login timestamp column 710, thecookie matcher 402 stores timestamps (e.g., the timestamp 220 of FIG. 2)indicative of when respective users logged in via partner login pages(e.g., the login page 204 of FIG. 2). In the partner user ID column 712,the cookie matcher 402 stores partner cookies (e.g., the partner Acookie 228 of FIG. 2).

Returning to FIG. 4, in the illustrated example, the apparatus 400 isprovided with the demographics associator 404 to associate demographicsinformation from the user accounts database 238 with correspondingpartner-based impressions from the partner-based impressions structure700. For example, the demographics associator 404 may retrievedemographics information for partner user IDs noted in the partner userID column 712 (FIG. 7) and associate the retrieved demographicsinformation with corresponding ones of the records in the partner-basedimpressions structure 700.

In the illustrated example of FIG. 4, to analyze demographic informationfor accuracy and/or completeness, the apparatus 400 is provided with thedemographics analyzer 406. In addition, to update, modify, and/orfill-in demographics information in inaccurate and/or incompleterecords, the apparatus 400 is provided with the demographics modifier408. In some examples, the demographics analyzer 406 and/or thedemographics modifier 408 analyze and/or adjust inaccurate demographicinformation using example methods, systems, apparatus, and/or articlesof manufacture disclosed in U.S. patent application Ser. No. 13/209,292,filed on Aug. 12, 2011, and titled “Methods and Apparatus to Analyze andAdjust Demographic Information,” which is hereby incorporated herein byreference in its entirety.

In the illustrated example, to remove user IDs from the partner-basedimpressions structure 700 after adding the demographics information andbefore providing the data to the AME 103, the apparatus 400 of theillustrated example is provided with a user ID modifier 410. In theillustrated example, the user ID modifier 410 is configured to at leastremove partner user IDs (from the partner user ID column 712) to protectthe privacy of registered users of the partner A database proprietor 104a. In some examples, the user ID modifier 410 may also remove the AMEuser IDs (e.g., from the AME user ID column 702) so that the impressionreports 106 a generated by the apparatus 400 are demographic-levelimpression reports. “Removal” of user IDs (e.g., by the user ID modifier410 and/or by the report generator 412) may be done by not providing acopy of the data in the corresponding user ID fields as opposed todeleting any data from those fields. If the AME user IDs are preservedin the impressions data structure 700, the apparatus 400 of theillustrated example can generate user-level impression reports.

In the illustrated example of FIG. 4, to generate the impression reports106 a, the apparatus 400 is provided with the report generator 412.Example information that the report generator 412 may generate for theimpression reports 106 a is described in detail below in connection withFIGS. 8 and 9.

In the illustrated example of FIG. 4, to parse information, theapparatus 400 is provided with the data parser 414. In some examples,the data parser 414 receives messages from client devices and/or othersystems and parses information from those received messages. Forexample, the apparatus 400 may use the data parser 414 to receive thelogin reporting message 118 from the cookie reporter 202 (FIG. 2) andparse out the partner A cookie 228, the AME cookie 208, and/or the logintimestamp 220 from the login reporting message 118. In some examples,the apparatus 400 also uses the data parser 414 to parse information inthe AME impression logs 122 and/or to parse information from any otherdata structure and/or message.

In the illustrated example of FIG. 4, to map information, the apparatus400 is provided with the mapper 416. In some examples, the mapper 416maps cookie identifiers associated with the same user but correspondingto different Internet domains. For example, the apparatus 400 may usethe mapper 416 to map the partner A cookie 228 to the AME cookie 208(FIG. 2) in the partner cookie map 236 (FIGS. 2, 4, and 5). In someexamples, the mapper 416 also maps login timestamps with correspondingcookie identifiers. For example, the apparatus 400 may use the mapper416 to map the login timestamp 220 (FIG. 2) with the correspondingpartner A cookie 228 and AME cookie 208 in the partner cookie map 236.

In the illustrated example of FIG. 4, to send computer executableinstructions to the client device(s) 108 to monitor user logins vialogin webpages (e.g., the login webpage 204 of FIG. 2), the apparatus400 is provided with the instructions interface 418. For example, theapparatus 400 may use the instructions interface 418 to send computerexecutable instructions (e.g., Java, java script, or any other computerlanguage or script) to the client device 108 that are executed by theweb browser 302 (FIG. 3) to implement the cookie reporter 202 (FIG. 2).In some examples, the instructions interface 418 sends the computerexecutable instructions to the client device 108 in response toreceiving a request from the web browser 302 for a login webpage (e.g.,the login webpage 204) of an Internet-based service provided by theentity (e.g., one of the database proprietor partners 104 a and 104 b)that implements the apparatus 400. In this manner, the client device 108can execute the computer executable instructions to monitor login eventsat the login webpage.

FIG. 15 is an example apparatus that may be used to implement theimpression monitor system 102 of FIGS. 1-3. In the illustrated example,to detect whether AME cookies (e.g., the AME cookie 208 of FIG. 2) havebeen set (e.g., are stored) in client devices (e.g., any of the clientdevices 108 of FIGS. 1-3), the impression monitor system 102 is providedwith a cookie status detector 1502. For example, the cookie statusdetector 1502 may inspect or analyze messages (e.g., the request 206 ofFIG. 2) from client devices to determine whether AME cookies are presenttherein. In the illustrated example, to generate AME cookies (e.g., theAME cookie 208 (FIG. 2)), the impression monitor system 102 is providedwith a cookie generator 1504.

In the illustrated example, to generate login timestamps (e.g., thelogin timestamp 220 of FIG. 2), the impression monitor system 102 isprovided with a timestamp generator 1506. For example, the timestampgenerator 1506 may be implemented using a real-time clock (RTC) or anyother timing or clock device or interface to track time and generatetimestamps. In the illustrated example, to generate messages (e.g., theresponse 216 of FIG. 2), the impression monitor system 102 is providedwith a message generator 1508. In the illustrated example, to logimpressions, the impression monitor system 102 is provided with animpression logger 1510. For example, the impression logger 1510 may logimpressions in the AME impression store 114 as shown in FIG. 6.

In the illustrated example, to receive messages and/or information fromclient devices 108 and send messages and/or information to clientdevices 108 and/or to partner database proprietors 104 a and 104 b, theimpression monitor system 102 is provided with a communication interface1512. For example, the communication interface 1512 may receive messagessuch as the tag requests 112 (FIG. 1) and the request 206 (FIG. 2) fromclient devices 108. Additionally, the communication interface 1512 maysend messages such as the response 216 (FIG. 2) to the client devices108 and send logged impressions (e.g., impressions logged in the AMEimpression store 114) to partner database proprietors 104 a and 104 b.

FIG. 16 is an example apparatus that may be used to implement a cookiereporter 202 of FIG. 2. In the illustrated example, to detect logevents, the cookie reporter 202 is provided with a login event detector1602. For example, the login detector 1602 may be configured to monitorlogin events generated by web browsers (e.g., the web browser 302 ofFIG. 3) of client devices (e.g., the client devices 108 of FIGS. 1-3).In the illustrated example, when a user logs in to the login webpage 204of FIG. 2, the login detector 1602 detects a login event.

In the illustrated example, to detect whether AME cookies (e.g., the AMEcookie 208 of FIG. 2) or partner cookies (e.g., the partner cookie 228of FIG. 2) have been set (e.g., are stored) in client devices (e.g., theclient devices 108 of FIGS. 1-3), the cookie reporter 202 is providedwith a cookie status detector 1604. For example, the cookie statusdetector 1602 may inspect or analyze cookie files or cookie entries inclient devices to determine whether AME cookies (e.g., the AME cookie208 of FIG. 2) or partner cookies (e.g., the partner cookie 228 of FIG.2) have been previously set. In the illustrated example, the cookiestatus detector 1604 may also determine whether cookies have expired. Inthe illustrated example, when a cookie expires, it is treated as invalidor as if it no longer exists in a client device and must be set again bya corresponding server domain.

In the illustrated example, to retrieve cookies from storage locationsin client devices (e.g., the client devices 108 of FIGS. 1-3), thecookie reporter 202 is provided with a cookie interface 1606. Forexample, the cookie interface 1606 may retrieve AME cookies (e.g., theAME cookie 208 of FIG. 2) or partner cookies (e.g., the partner cookie228 of FIG. 2) from their respective storage locations in clientdevices. In addition, the cookie interface 1606 may also store cookiesset by and received from the impression monitor system 102 and/or anypartner database proprietor in the client devices.

In the illustrated example, to generate messages (e.g., the tag requests112 of FIGS. 1 and 3, the log reporting messages 118 of FIGS. 1 and 2,and the request 206 of FIG. 2), the cookie reporter 202 is provided witha message generator 1608. In the illustrated example, to send messagesand/or information to the impression monitor system 102 and/or topartner database proprietors (e.g., the partner database proprietors 104a and 104 b of FIGS. 1 and 2) and/or to receive messages and/orinformation from the impression monitor system 102, the cookie reporter202 is provided with a communication interface 1610. For example, thecommunication interface 1610 may send the tag requests 112 (FIGS. 1 and3) and the request 206 of FIG. 2 to the impression monitor system 102,receive the response 216 (FIG. 2) from the impression monitor system102, and send the login reporting messages 118 (FIGS. 1 and 2) to thepartner database proprietors 104 a and 104 b.

While example manners of implementing the apparatus 102 and 202 havebeen illustrated in FIGS. 15 and 16, one or more of the elements,processes and/or devices illustrated in FIGS. 15 and 16 may be combined,divided, re-arranged, omitted, eliminated and/or implemented in anyother way. Further, the cookie status detector 1502, the cookiegenerator 1504, the timestamp generator 1506, the message generator1508, the impression logger 1510, the communication interface 1512and/or, more generally, the example apparatus 102 of FIG. 15 may beimplemented by hardware, software, firmware and/or any combination ofhardware, software and/or firmware. In addition, the login eventdetector 1602, the cookie status detector 1604, the cookie interface1606, the message generator 1608, the communication interface 1610and/or, more generally, the example apparatus 202 of FIG. 16 may beimplemented by hardware, software, firmware and/or any combination ofhardware, software and/or firmware. Thus, for example, any of the cookiestatus detector 1502, the cookie generator 1504, the timestamp generator1506, the message generator 1508, the impression logger 1510, thecommunication interface 1512 and/or, more generally, the exampleapparatus 102 and/or any of the login event detector 1602, the cookiestatus detector 1604, the cookie interface 1606, the message generator1608, the communication interface 1610 and/or, more generally, theexample apparatus 202 could be implemented by one or more circuit(s),programmable processor(s), application specific integrated circuit(s)(ASIC(s)), programmable logic device(s) (PLD(s)) and/or fieldprogrammable logic device(s) (FPLD(s)), etc. When any of the apparatusor system claims of this patent are read to cover a purely softwareand/or firmware implementation, at least one of the cookie statusdetector 1502, the cookie generator 1504, the timestamp generator 1506,the message generator 1508, the impression logger 1510, thecommunication interface 1512, the login event detector 1602, the cookiestatus detector 1604, the cookie interface 1606, the message generator1608, and/or the communication interface 1610 are hereby expresslydefined to include a tangible computer readable medium such as a memory,DVD, CD, BluRay disk, etc. storing the software and/or firmware. Furtherstill, the example apparatus 102 and 202 may include one or moreelements, processes and/or devices in addition to, or instead of, thoseillustrated in FIGS. 15 and 16, and/or may include more than one of anyor all of the illustrated elements, processes and devices.

Turning to FIG. 8, an example impressions totalization data structure800, which may be generated by the report generator 412 of FIG. 4,stores impression totalizations based on the impressions logged by theimpression monitor system 102 (FIGS. 1-3). As shown in FIG. 8, theimpressions totalization structure 800 shows quantities of impressionslogged for the client devices 108 (FIGS. 1-3). In the illustratedexample, the impressions totalization structure 800 is generated by thereport generator 412 for an advertisement campaign (e.g., one or more ofthe advertisements 110 of FIG. 1) to determine frequencies ofimpressions per day for each monitored user.

To track frequencies of impressions per unique user per day, theimpressions totalization structure 800 is provided with a frequencycolumn 802. A frequency of 1 indicates one exposure per day of an adcampaign to a unique user, while a frequency of 4 indicates fourexposures per day of the same ad campaign to a unique user. To track thequantity of unique users to which impressions are attributable, theimpressions totalization structure 800 is provided with a UUIDs column804. A value of 100,000 in the UUIDs column 804 is indicative of 100,000unique users. Thus, the first entry of the impressions totalizationstructure 800 indicates that 100,000 unique users (i.e., UUIDs=100,000)were exposed once (i.e., frequency=1) in a single day to a particular adcampaign.

To track impressions based on exposure frequency and UUIDs, theimpressions totalization structure 800 is provided with an impressionscolumn 806. Each impression count stored in the impressions column 806is determined by multiplying a corresponding frequency value stored inthe frequency column 802 with a corresponding UUID value stored in theUUID column 804. For example, in the second entry of the impressionstotalization structure 800, the frequency value of two is multiplied by200,000 unique users to determine that 400,000 impressions areattributable to a particular ad campaign.

Turning to FIG. 9, an ad campaign-level age/gender and impressioncomposition data structure 900 is shown, which, in the illustratedexample, may be generated by the report generator 412 of FIG. 4. Theimpression data in the ad campaign-level age/gender and impressioncomposition structure 900 of FIG. 9 corresponds to impressionsattributable to registered user of a particular partner database (DB)proprietor (e.g., the partner A database proprietor 104 a of FIGS. 1 and2 or the partner B database proprietor 104 b of FIG. 1). Similar tablescan be generated for content and/or other media. Additionally oralternatively, other media in addition to advertisements may be added tothe data structure 900.

The ad campaign-level age/gender and impression composition structure900 is provided with an age/gender column 902, an impressions column904, a frequency column 906, and an impression composition column 908.The age/gender column 902 of the illustrated example indicates differentage/gender demographic groups. The impressions column 904 of theillustrated example stores values indicative of the total impressionsfor a particular ad campaign for corresponding age/gender demographicgroups. The frequency column 906 of the illustrated example storesvalues indicative of the frequency of exposure per user for the adcampaign that contributed to the impressions in the impressions column904. The impressions composition column 908 of the illustrated examplestores the percentage of impressions for each of the age/genderdemographic groups.

In some examples, the demographics analyzer 406 and the demographicsmodifier 408 of FIG. 4 perform demographic accuracy analyses andadjustment processes on demographic information before tabulating finalresults of impression-based demographic information in thecampaign-level age/gender and impression composition table 900. This canbe done to address a problem facing online audience measurementprocesses in that the manner in which registered users representthemselves to online database proprietors (e.g., the partners 104 a and104 b) is not necessarily veridical (e.g., truthful and/or accurate). Insome instances, example approaches to online measurements that leverageaccount registrations at such online database proprietors to determinedemographic attributes of an audience may lead to inaccuratedemographic-exposure results if they rely on self-reporting ofpersonal/demographic information by the registered users during accountregistration at the database proprietor site. There may be numerousreasons for why users report erroneous or inaccurate demographicinformation when registering for database proprietor services. Theself-reporting registration processes used to collect the demographicinformation at the database proprietor sites (e.g., social media sites)does not facilitate determining the veracity of the self-reporteddemographic information. In some examples, to analyze and/or adjustinaccurate demographic information, the demographics analyzer 406 and/orthe demographics modifier 408 may use example methods, systems,apparatus, and/or articles of manufacture disclosed in U.S. patentapplication Ser. No. 13/209,292, filed on Aug. 12, 2011, and titled“Methods and Apparatus to Analyze and Adjust Demographic Information,”which is hereby incorporated herein by reference in its entirety.

Although the example ad campaign-level age/gender and impressioncomposition structure 900 shows impression statistics in connection withonly age/gender demographic information, the report generator 412 ofFIG. 4 may generate the same or other data structures to additionally oralternatively include other types of demographic information. In thismanner, the report generator 412 can generate the impression reports 106a (FIGS. 1 and 4) to reflect impressions based on different types ofdemographics and/or different types of media.

FIGS. 10-13 are flow diagrams representative of machine readableinstructions that can be executed to implement the apparatus and systemsof FIGS. 1, 2, 3, and/or 4. The example processes of FIGS. 10-13 may beimplemented using machine readable instructions that, when executed,cause a device (e.g., a programmable controller or other programmablemachine or integrated circuit) to perform the operations shown in FIGS.10-13. In this example, the machine readable instructions comprise aprogram for execution by a processor such as the processor 1412 shown inthe example computer 1410 discussed below in connection with FIG. 14.The program may be embodied in software stored on a tangible computerreadable medium such as a CD-ROM, a floppy disk, a hard drive, a digitalversatile disk (DVD), a BluRay disk, a flash memory, a read-only memory(ROM), a random-access memory (RAM), or a memory associated with theprocessor 1412, but the entire program and/or parts thereof couldalternatively be executed by a device other than the processor 1412and/or embodied in firmware or dedicated hardware.

As used herein, the term tangible computer readable medium is expresslydefined to include any type of computer readable storage and to excludepropagating signals. Additionally or alternatively, the exampleprocesses of FIGS. 10-13 may be implemented using coded instructions(e.g., computer readable instructions) stored on a non-transitorycomputer readable medium such as a flash memory, a read-only memory(ROM), a random-access memory (RAM), a cache, or any other storage mediain which information is stored for any duration (e.g., for extended timeperiods, permanently, brief instances, for temporarily buffering, and/orfor caching of the information). As used herein, the term non-transitorycomputer readable medium is expressly defined to include any type ofcomputer readable medium and to exclude propagating signals. As usedherein, when the phrase “at least” is used as the transition term in apreamble of a claim, it is open-ended in the same manner as the term“comprising” is open ended. Thus, a claim using “at least” as thetransition term in its preamble may include elements in addition tothose expressly recited in the claim.

Alternatively, the example processes of FIGS. 10-13 may be implementedusing any combination(s) of application specific integrated circuit(s)(ASIC(s)), programmable logic device(s) (PLD(s)), field programmablelogic device(s) (FPLD(s)), discrete logic, hardware, firmware, etc.Also, the example processes of FIGS. 10-13 may be implemented as anycombination(s) of any of the foregoing techniques, for example, anycombination of firmware, software, discrete logic and/or hardware.

Although the example processes of FIGS. 10-13 are described withreference to the flow diagrams of FIGS. 10-13, other methods ofimplementing the apparatus and systems of FIGS. 1, 2, 3, and/or 4 may beemployed. For example, the order of execution of the blocks may bechanged, and/or some of the blocks described may be changed, eliminated,sub-divided, or combined. Additionally, one or both of the exampleprocesses of FIGS. 10-13 may be performed sequentially and/or inparallel by, for example, separate processing threads, processors,devices, discrete logic, circuits, etc.

Turning in detail to FIG. 10, the depicted example processes may be usedto report login events and user cookies (e.g., the AME cookie 208 andthe partner A cookie 228 of FIGS. 2 and 3) to database proprietors(e.g., the partner A database proprietor 104 a of FIGS. 1 and 2). In theillustrated example, the flow diagram shows a client device process 1002and an impression monitor system process 1004. In the illustratedexample, the client device process 1002 may be performed by the cookiereporter 202 of FIGS. 2 and 16, and the impression monitor systemprocess 1004 may be implemented by the impression monitor system 102 ofFIGS. 1-3 and 15. The example processes of FIG. 10 are described inconnection with FIG. 2 as interactions between the client device 108,the impression monitor system 102, and the partner A database proprietor104 a. However, processes similar or identical to the example processesof FIG. 10 may be performed at any time or at the same time betweenother client devices, the impression monitor system 102 and/or otherdatabase proprietors to accomplish the same type of user login reportingevents when users login to login pages (e.g., the login page 204 of FIG.2) of respective database proprietors (e.g., the database proprietors104 a and 104 b of FIGS. 1 and 2).

Initially, as part of the client device process 1002, the login eventdetector 1602 (FIG. 16) detects a login event (block 1006). The loginevent may be, for example, a user of the client device 108 logging intothe login page 204 of FIG. 2. The message generator 1608 (FIG. 16)generates the request 206 (FIG. 2) to indicate the login event (block1008). The cookie status detector 1604 (FIG. 16) determines whether anAME cookie (e.g. the AME cookie 208 of FIG. 2) is already set in theclient device 108 (block 1010). If the AME cookie 208 is already set,the cookie interface 1606 (FIG. 16) and/or the message generator 1608store(s) the AME cookie 208 (e.g., a name-value pair identifying a user)in the request 206 (block 1012). After storing the AME cookie 208 in therequest 206 (block 1012) or if the AME cookie 208 is not already set inthe client device (block 1010), the communication interface 1610 (FIG.16) sends the request 206 to the impression monitor system 102 (block1014).

As shown in the example impression monitor system process 1004, thecommunication interface 1512 (FIG. 15) receives the request 206 (block1016), and the cookie status detector 1502 (FIG. 15) determines whetherthe AME cookie 208 is already set in the client device 108 (block 1018).For example, the cookie status detector 1502 can determine whether theAME cookie 208 is already set based on whether the request 206 containsthe AME cookie 208. If the cookie status detector 1502 determines thatthe AME cookie 208 is not already set (block 1018), the cookie generator1504 (FIG. 15) creates the AME cookie 208 (block 1020). For example, thecookie generator 1504 can generate the AME cookie 208 by generating aUUID for the client device 108. The message generator 1508 (FIG. 15)stores the AME cookie 208 in the response 216 (FIG. 2) (block 1022).

After storing the AME cookie 208 in the response 216 (block 1022) or ifthe cookie status detector 1502 determines at block 1018 that the AMEcookie 208 is already set in the client device 108, the timestampgenerator 1506 generates a login timestamp (e.g., the login timestamp220 of FIG. 2) (block 1024) to indicate a login time for the detectedlogin event. The message generator 1508 stores the login timestamp 220in the response 216 (block 1026), and the communication interface 1512sends the response 216 to the client device 108 (block 1028).

Returning to the client device process 1002, the communication interface1610 (FIG. 16) receives the response 216 (block 1030), and the messagegenerator 1608 (FIG. 16) generates the login reporting message 118(FIGS. 1 and 2) (block 1032). If present, the cookie interface 1606(FIG. 16) and/or the message generator 1608 store(s) a partner cookiecorresponding to the login event detected at block 1006 (e.g., thepartner A cookie 228) in the login reporting message 118 (block 1034).If a corresponding partner cookie is not present in the client device108, a partner cookie is not stored in the login reporting message 118to indicate to the corresponding partner that it should create a partnercookie for the client device 108. In addition, the cookie interface 1606and/or the message generator 1608 store(s) the AME cookie 208 as a dataparameter (e.g., in the payload 232) in the login reporting message 118(block 1036). The message generator 1608 also stores the login timestamp220 in the login reporting message 118 (e.g., in the payload 232) (block1038). The communication interface 1610 sends the login reportingmessage 118 to a corresponding partner database proprietor (e.g., thepartner A database proprietor 104 a) (block 1040). In this manner, thecookie reporter 202 enables the partner A database proprietor 104 a tomap the partner A cookie 228 to the AME cookie 208 and the logintimestamp 220 in the partner cookie map 236 of FIGS. 2 and 5. Theexample process of FIG. 10 then ends.

Turning now to FIG. 11, the depicted flow diagram is representative ofan example process that may be performed by a partner databaseproprietor (e.g., the partner database proprietors 104 a and/or 104 b ofFIGS. 1 and 2) to map AME cookie identifiers (e.g., a UUID of the AMEcookie 208 of FIG. 2) with user identifiers (e.g., a UUID of the partnerA cookie 228 of FIG. 2) of users registered with the partner databaseproprietor. While for simplicity, FIG. 11 refers to a process receivinga single login message, many such processes may exist and execute inparallel (e.g., parallel threads). The example process of FIG. 11 isdescribed in connection with the illustrated example of FIG. 2, theapparatus 400 of FIG. 4, and the partner A database proprietor 104 a.However, processes similar or identical to the example processes of FIG.11 may be performed at any time or at the same time by other partnerdatabase proprietors and/or other apparatus to accomplish the same typeof cookie mapping process.

Initially, the partner A database proprietor 104 a receives the loginreporting message 118 (FIGS. 1 and 2) (block 1102). The data parser 414(FIG. 4) extracts the partner A cookie 228 (block 1104) from the loginreporting message 118. In the illustrated example, the data parser 414extracts the partner A cookie 228 from the cookie field 230 of the loginreporting message 118. The data parser 414 extracts the AME cookie 208(block 1106) from the login reporting message 118. In the illustratedexample, the data parser 414 extracts the AME cookie 208 as a dataparameter from the payload 232 of the login reporting message 118. Inaddition, the data parser 414 extracts the login timestamp 220 from thelogin reporting message 118 (block 1108). The mapper 416 (FIG. 4) mapsthe partner A cookie 228 to the AME cookie 208 (e.g., maps the UUIDs ofeach cookie to one another) (block 1110) in, for example, the partnercookie map 236 of FIGS. 2 and 5. In addition, the mapper 416 stores thelogin timestamp 220 in association with the mapped cookies (block 1112)in the partner cookie map 236. The example process of FIG. 11 then ends.

Now turning to FIG. 12, the depicted example process may be performed tolog impressions. In the illustrated example, the example process of FIG.12 is described in connection with FIGS. 3 and 15 as being performed bythe impression monitor system 102 based on tag requests received fromthe client device 108. However, processes similar or identical to theexample process of FIG. 12 may be performed at any time or at the sametime (e.g., multiple threads may be spawned and execute in parallel) bythe impression monitor system 102 in connection with other clientdevices (e.g., any of the client devices 108 of FIG. 1 or any otherclient devices) to log impressions attributable to those client devices.

Initially, the communication interface 1512 (FIG. 15) receives a tagrequest (e.g., the tag request 112 of FIGS. 1 and 3) (block 1202). Theimpression logger 1510 (FIG. 15) logs an impression for an AME UUIDindicated by the AME cookie 208 (block 1204). In the illustratedexample, the impression logger 1510 logs the impression in the AMEimpression store 114 of FIGS. 1, 3, and 6. The impression logger 1510determines whether it should send the AME impression logs 122 (FIGS. 1and 4) to one or more partner database proprietors (block 1206). Forexample, the impression logger 1510 may be configured to periodically oraperiodically send the AME impression logs 122 to one or more partnerdatabase proprietors (e.g., the partner database proprietors 104 a and104 b of FIGS. 1 and 2) based on one or more of a schedule and/or athreshold of logged impressions.

If the impression logger 1510 determines that it should send the AMEimpression logs 122 to one or more partner database proprietors (block1206), the communication interface 1512 sends the AME impression logs122 to the one or more partner database proprietors (block 1208). Inresponse, the communication interface 1512 receives one or moreimpression reports (e.g., the impression reports 106 a and 106 b ofFIGS. 1 and 4) from the one or more partner database proprietors (block1210). In some examples, the impression monitor system 102 appliesweighting factors to impression audience data in impression reports fromdifferent database proprietors (e.g., the partner database proprietors104 a and 104 b). In some examples, the weighting factors are determinedfor each database proprietor based on, for example, demographicdistributions and/or impression distributions in the impression dataand/or sample sizes (e.g., the quantity of registered users of aparticular database proprietor, the quantity of registered usersmonitored for the particular database proprietor, and/or the quantity ofimpressions logged by the AME 103 for registered users of the particulardatabase proprietor).

After receiving the one or more impression reports (block 1210) or if atblock 1206 the impression logger 1510 determines that it should not sendthe AME impression logs 122 to one or more partner database proprietors,the impression monitor system 102 determines whether it should continueto monitor impressions (block 1212). For example, the impression monitorsystem 102 may be configured to monitor impressions until it is turnedoff or disabled. If the impression monitor system 102 determines that itshould continue to monitor impressions (block 1212), control returns toblock 1202. Otherwise, the example process of FIG. 12 ends.

Turning now to FIG. 13, the depicted example process may be used togenerate demographics-based impressions reports (e.g., the impressionreports 106 a and 106 b of FIGS. 1 and 4). The example process of FIG.13 is described in connection with FIG. 4 as being implemented by theexample apparatus 400 via the partner A database proprietor 104 a.However, processes similar or identical to the example process of FIG.13 may be performed at any time or at the same time by any other partnerdatabase proprietor(s) to generate impression reports based onregistered users of those partner database proprietor(s).

Initially, the apparatus 400 receives the AME impression logs 122 (FIG.4) (block 1302). The cookie matcher 402 (FIG. 4) matches AME cookies topartner database proprietor cookies (block 1304). For example, thecookie matcher 402 can use a cookie map of the corresponding databaseproprietor (e.g., the partner A cookie map 236 (FIG. 4)) to match UUIDsfrom AME cookies (e.g., the AME cookie 208 of FIGS. 2 and 3) indicatedin the AME impression logs 122 to UUIDs from partner database proprietorcookies (e.g., the partner A database proprietor cookie 228 of FIGS. 2and 3). The cookie matcher 402 then associates impressions (e.g.,impressions noted in the AME impression logs 122) to correspondingpartner database proprietor UUIDs (block 1306) based on matches found atblock 1304. For example, the cookie matcher 402 may generate thepartner-based impressions data structure 700 described above inconnection with FIG. 7.

The demographics associator 404 (FIG. 4) associates demographics ofregistered users of the corresponding database proprietor (e.g., thepartner A database proprietor 104 a) to the impressions (block 1308).For example, the demographics associator 404 may retrieve demographicsinformation from the user accounts database 238 (FIGS. 2 and 4) forpartner user IDs noted in the partner user ID column 712 of thepartner-based impressions data structure 700.

The user ID modifier 410 removes user IDs from the demographics-basedimpressions data structure 700 (block 1310). For example, the user IDmodifier 410 can remove UUIDs from the AME user ID column 702corresponding to AME cookies (e.g., the AME cookie 208 of FIGS. 2 and 3)and the partner user ID column 712 corresponding to partner cookies(e.g., the partner A cookie 228 of FIGS. 2 and 3). In other examples,the report generator 412 can copy selected portions from thedemographics-based impressions data structure 700 and store the selectedportions in a report without copying over the user IDs. In this manner,the apparatus 400 can obfuscate identities of registered users toprotect their privacy when the demographics-based impressions are sharedwith others (e.g., an audience measurement entity).

The demographics analyzer 406 (FIG. 4) analyzes the demographicsinformation (block 1312) that was associated with the impressions atblock 1308. The demographics analyzer 406 determines whether anydemographics information needs to be modified (block 1314). If any ofthe demographics information needs to be modified (e.g., demographicsinformation needs to be changed or added due to being incomplete and/orinaccurate), the demographics modifier 408 (FIG. 4) modifies selectdemographics data needing modification (block 1316). In the illustratedexample, the demographics analyzer 406 and/or the demographics modifier408 may perform the operations of blocks 1312, 1314, and 1316 to analyzeand/or modify demographics information using, for example, one or moreexample techniques disclosed in U.S. patent application Ser. No.13/209,292, filed on Aug. 12, 2011, and titled “Methods and Apparatus toAnalyze and Adjust Demographic Information,” which is herebyincorporated herein by reference in its entirety.

After modifying demographics information at block 1316 or if at block1314 the demographics analyzer 406 determines that none of thedemographics information requires modification, the report generator 412generates one or more impression reports (e.g., the impression reports106 a of FIGS. 1 and 4) (block 1318). For example, the report generator412 may generate one or more of the impression reports 106 a using oneor more example techniques described above in connection with FIGS. 8and 9 and/or using any other suitable technique(s). The apparatus 400then sends the one or more impression reports 106 a to the impressionmonitor system 102 (block 1320). In the illustrated example, theimpression reports 106 a are indicative of demographic segments,populations, or groups associated with different AME cookies 208 (andcorresponding partner A cookies 228) and that were exposed to content(e.g., advertisements and/or other media) identified by campaign IDsand/or other the media content IDs. The example process of FIG. 13 thenends.

FIG. 14 is a block diagram of an example processor system 1410 that maybe used to implement the example apparatus, methods, and systemsdisclosed herein. As shown in FIG. 14, the processor system 1410includes a processor 1412 that is coupled to an interconnection bus1414. The processor 1412 may be any suitable processor, processing unit,or microprocessor. Although not shown in FIG. 14, the system 1410 may bea multi-processor system and, thus, may include one or more additionalprocessors that are identical or similar to the processor 1412 and thatare communicatively coupled to the interconnection bus 1414.

The processor 1412 of FIG. 14 is coupled to a chipset 1418, whichincludes a memory controller 1420 and an input/output (I/O) controller1422. A chipset provides I/O and memory management functions as well asa plurality of general purpose and/or special purpose registers, timers,etc. that are accessible or used by one or more processors coupled tothe chipset 1418. The memory controller 1420 performs functions thatenable the processor 1412 (or processors if there are multipleprocessors) to access a system memory 1424, a mass storage memory 1425,and/or an optical media 1427.

In general, the system memory 1424 may include any desired type ofvolatile and/or non-volatile memory such as, for example, static randomaccess memory (SRAM), dynamic random access memory (DRAM), flash memory,read-only memory (ROM), etc. The mass storage memory 1425 may includeany desired type of mass storage device including hard disk drives,optical drives, tape storage devices, etc. The optical media 1427 mayinclude any desired type of optical media such as a digital versatiledisc (DVD), a compact disc (CD), or a blu-ray optical disc. Theinstructions of any of FIGS. 10-13 may be stored on any of the tangiblemedia represented by the system memory 1424, the mass storage device1425, the optical media 1427, and/or any other media.

The I/O controller 1422 performs functions that enable the processor1412 to communicate with peripheral input/output (I/O) devices 1426 and1428 and a network interface 1430 via an I/O bus 1432. The I/O devices1426 and 1428 may be any desired type of I/O device such as, forexample, a keyboard, a video display or monitor, a mouse, etc. Thenetwork interface 1430 may be, for example, an Ethernet device, anasynchronous transfer mode (ATM) device, an 802.11 device, a digitalsubscriber line (DSL) modem, a cable modem, a cellular modem, etc. thatenables the processor system 1410 to communicate with another processorsystem.

While the memory controller 1420 and the I/O controller 1422 aredepicted in FIG. 14 as separate functional blocks within the chipset1418, the functions performed by these blocks may be integrated within asingle semiconductor circuit or may be implemented using two or moreseparate integrated circuits.

Although the above discloses example methods, apparatus, systems, andarticles of manufacture including, among other components, firmwareand/or software executed on hardware, it should be noted that suchmethods, apparatus, systems, and articles of manufacture are merelyillustrative and should not be considered as limiting. Accordingly,while the above describes example methods, apparatus, systems, andarticles of manufacture, the examples provided are not the only ways toimplement such methods, apparatus, systems, and articles of manufacture.

Although certain example methods, apparatus and articles of manufacturehave been described herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe claims of this patent.

What is claimed is:
 1. A method to log media impressions, the methodcomprising: extracting first and second cookie identifiers from amessage received at a first Internet domain from a client device, thefirst cookie identifier associated with the first Internet domain, andthe second cookie identifier associated with a second Internet domainoutside the first Internet domain; and mapping the first cookieidentifier to the second cookie identifier.
 2. The method as defined inclaim 1, further including mapping a login timestamp to the first andsecond cookie identifiers, the login timestamp indicative of a time atwhich a login event occurred at a webpage associated with the firstInternet domain.
 3. The method as defined in claim 1, wherein themessage is received from a client device in response to a login event atthe client device in association with an Internet-based service of thefirst Internet domain.
 4. The method as defined in claim 3, furtherincluding sending computer executable instructions to the client device,the computer executable instructions to cause the client device to sendthe message in response to detecting the login event.
 5. The method asdefined in claim 4, further including sending the computer executableinstructions in response to receiving a request for a login webpage ofan Internet-based service associated with the first Internet domain. 6.An apparatus to log media impressions, the apparatus comprising: a dataparser to extract first and second cookie identifiers from a messagereceived at a first Internet domain from a client device, the firstcookie identifier associated with the first Internet domain, and thesecond cookie identifier associated with a second Internet domainoutside the first Internet domain; and a mapper to map the first cookieidentifier to the second cookie identifier.
 7. The apparatus as definedin claim 6, wherein the mapper is further to map a login timestamp tothe first and second cookie identifiers, the login timestamp indicativeof a time at which a login event occurred at a webpage associated withthe first Internet domain.
 8. The apparatus as defined in claim 6,wherein the message is received from a client device in response to alogin event at the client device in association with an Internet-basedservice of the first Internet domain.
 9. The apparatus as defined inclaim 8, further including an instructions interface to send computerexecutable instructions to the client device, the computer executableinstructions to cause the client device to send the message in responseto detecting the login event.
 10. The apparatus as defined in claim 9,wherein the instructions interface is further to send the computerexecutable instructions in response to receiving a request for a loginwebpage of an Internet-based service associated with the first Internetdomain.
 11. A tangible computer readable medium comprising instructionsthat, when executed, cause a machine to at least: extract first andsecond cookie identifiers from a message received at a first Internetdomain from a client device, the first cookie identifier associated withthe first Internet domain, and the second cookie identifier associatedwith a second Internet domain outside the first Internet domain; and mapthe first cookie identifier to the second cookie identifier.
 12. Thecomputer readable medium as defined in claim 11, wherein theinstructions are further to cause the machine to map a login timestampto the first and second cookie identifiers, the login timestampindicative of a time at which a login event occurred at a webpageassociated with the first Internet domain.
 13. The computer readablemedium as defined in claim 11, wherein the message is received from aclient device in response to a login event at the client device inassociation with an Internet-based service of the first Internet domain.14. The computer readable medium as defined in claim 13, wherein theinstructions further cause the machine to send computer executableinstructions to the client device, the computer executable instructionsto cause the client device to send the message in response to detectingthe login event.
 15. The computer readable medium as defined in claim14, wherein the instructions further cause the machine to send thecomputer executable instructions in response to receiving a request fora login webpage of an Internet-based service associated with the firstInternet domain.